About Me
I am the CTO at Think Therapeutics. Previously, I completed my Ph.D. in Computer Science at MIT CSAIL advised by Prof. David Gifford. I developed methods to interpret deep neural networks and design therapeutics using machine learning.
Prior to that, I was an undergrad (MIT '17) and MEng student at MIT. I double majored in computer science and mathematics and minored in economics.
I have had the pleasure to work at Google Brain, Facebook, Bloomberg LP, KAYAK, and Leiden University.
I am originally from Long Island, New York. In my free time I enjoy skiing and sailing.
Publications
A pan-variant mRNA-LNP T cell vaccine protects HLA transgenic mice from mortality after infection with SARS-CoV-2 Beta
Brandon Carter*, Pinghan Huang*, Ge Liu, Yuejin Liang, Paulo J.C. Lin, Bi-Hung Peng, Lindsay G. A. McKay, Alexander Dimitrakakis, Jason Hsu, Vivian Tat, Panatda Saenkham-Huntsinger, Jinjin Chen, Clarety Kaseke, Gaurav D. Gaiha, Qiaobing Xu, Anthony Griffiths, Ying K. Tam, Chien-Te K. Tseng, David K. Gifford
Frontiers in Immunology, 2023
[Press – MIT News] [Press – Boston Globe]
Maximum n-times Coverage for Vaccine Design
Ge Liu, Alexander Dimitrakakis, Brandon Carter, David Gifford
International Conference on Learning Representations (ICLR), 2022
[Code]
Embedding Comparator: Visualizing Differences in Global Structure and Local Neighborhoods via Small Multiples
Angie Boggust*, Brandon Carter*, Arvind Satyanarayan
International Conference on Intelligent User Interfaces (IUI), 2022
[Demo] [Video] [Code]
Using Deep Learning to Classify the Protein Universe
Maxwell Bileschi, David Belanger, Drew Bryant, Theo Sanderson, Brandon Carter, D. Sculley, Alex Bateman, Mark DePristo, Lucy Colwell
Nature Biotechnology, 2022
[Press]
Overinterpretation reveals image classification model pathologies
Brandon Carter, Siddhartha Jain, Jonas Mueller, David Gifford
Advances in Neural Information Processing Systems (NeurIPS), 2021
[Press]
[Code]
Predicted Cellular Immunity Population Coverage Gaps for SARS-CoV-2 Subunit Vaccines and their Augmentation by Compact Peptide Sets
Ge Liu, Brandon Carter, David Gifford
Cell Systems, 2021
[Press]
[Code]
Machine learning optimization of MHC class II presented peptides
Zheng Dai*, Brooke Huisman*, Haoyang Zeng, Brandon Carter, Siddhartha Jain, Michael Birnbaum, David Gifford
Bioinformatics, 2021
[Featured as spotlight talk at MLCB 2019]
Lost in Pruning: The Effects of Pruning Neural Networks beyond Test Accuracy
Lucas Liebenwein, Cenk Baykal, Brandon Carter, David Gifford, Daniela Rus
Machine Learning and Systems (MLSys), 2021
[Code]
Computationally Optimized SARS-CoV-2 MHC Class I and II Vaccine Formulations Predicted to Target Human Haplotype Distributions
Ge Liu*, Brandon Carter*, Trenton Bricken, Siddhartha Jain, Mathias Viard, Mary Carrington, David Gifford
Cell Systems, 2020
[Press]
[Code]
Antibody complementarity determining region design using high-capacity machine learning
Ge Liu*, Haoyang Zeng*, Jonas Mueller, Brandon Carter, Ziheng Wang, Jonas Schilz, Geraldine Horny, Michael Birnbaum, Stefan Ewert, David Gifford
Bioinformatics, 2020
[Code]
What made you do this? Understanding black-box decisions with sufficient input subsets
Brandon Carter*, Jonas Mueller*, Siddhartha Jain, David Gifford
Artificial Intelligence and Statistics (AISTATS), 2019
[Featured as contributed talk at NeurIPS 2018 Workshop on Interpretability and Robustness] [Slides] [Lecture notes] [Code]
Critiquing Protein Family Classification Models Using Sufficient Input Subsets
Brandon Carter, Maxwell Bileschi, Jamie Smith, Theo Sanderson, Drew Bryant, David Belanger, Lucy Colwell
Journal of Computational Biology, 2019
[Featured as spotlight talk at ICML 2019 Workshop on Computational Biology] [Slides]
Survey of Fully Verifiable Voting Cryptoschemes
Brandon Carter, Kenneth Leidal, Devin Neal, Zachary Neely
MIT Computer and Network Security (6.857) Final Project, 2016
Safety and Efficacy of Ganciclovir Ophthalmic Gel for Treatment of Adenovirus Keratoconjunctivitis Utilizing Cell Culture and Animal Models
Seth Epstein, Karen Fernandez, Brandon Carter, Salma Abdou, Neha Gadaria, Penny Asbell
Investigative Ophthalmology and Visual Science (IOVS), 2012
Interpretations of Machine Learning and Their Application to Therapeutic Design
Brandon Carter
Ph.D. Thesis, MIT Dept. of Electrical Engineering and Computer Science, 2023
Interpreting Black-Box Models Through Sufficient Input Subsets
Brandon Carter
M.Eng. Thesis, MIT Dept. of Electrical Engineering and Computer Science, 2019
* Equal Contribution
Full listing in Google Scholar.
Contact
My email is bcarter [at] csail [dot] mit [dot] edu.